Related papers: On the Lack of Consensus Among Technical Debt Dete…
Kubernetes is a tool that facilitates rapid deployment of software. Unfortunately, configuring Kubernetes is prone to errors. Configuration defects are not uncommon and can result in serious consequences. This paper reports an empirical…
This paper is a reproduction of work by Ray et al. which claimed to have uncovered a statistically significant association between eleven programming languages and software defects in projects hosted on GitHub. First we conduct an…
Building meaningful interoperation with external software units requires performing the conceptual interoperability analysis that starts with identifying the conceptual interoperability constraints of each software unit, then it compares…
Token-inconsistency bugs (TIBs) involve the misuse of syntactically valid yet incorrect code tokens, such as misused variables and erroneous function invocations, which can often lead to software bugs. Unlike simple syntactic bugs, TIBs…
For large-scale simulation codes with huge and complex code bases, where bit-for-bit comparisons are too restrictive, finding the source of statistically significant discrepancies (e.g., from a previous version, alternative hardware or…
In recent years, the importance of smart contract security has been heightened by the increasing number of attacks against them. To address this issue, a multitude of static application security testing (SAST) tools have been proposed for…
Modern software is developed under considerable time pressure, which implies that developers more often than not have to resort to compromises when it comes to code that is well written and code that just does the job. This has led over the…
In current research, there are contrasting results about the applicability of software source code metrics as features for defect prediction models. The goal of the paper is to evaluate the adoption of software metrics in models for…
Technical Debts (TD) are problems of the internal software quality. They are often contracted due to tight project deadlines, for example quick fixes and workarounds, and can make future changes more costly or impossible. TD prevention…
This study explores the dynamic landscape of Technical Debt (TD) topics in software engineering by examining its evolution across time, programming languages, and repositories. Despite the extensive research on identifying and quantifying…
In recent years, researchers have developed a number of tools to conduct taint analysis of Android applications. While all the respective papers aim at providing a thorough empirical evaluation, comparability is hindered by varying or…
Modern software relies on a multitude of automated testing and quality assurance tools to prevent errors, bugs and potential vulnerabilities. This study sets out to provide a head-to-head, quantitative and qualitative evaluation of six…
Complexity of products, volatility in global markets, and the increasingly rapid pace of innovations may make it difficult to know how to approach challenging situations in mechatronic design and production. Technical Debt (TD) is a…
As software projects progress, quality of code assumes paramount importance as it affects reliability, maintainability and security of software. For this reason, static analysis tools are used in developer workflows to flag code quality…
Background: Software security is crucial to ensure that the users are protected from undesirable consequences such as malware attacks which can result in loss of data and, subsequently, financial loss. Technical Debt (TD) is a metaphor…
Over time, software systems suffer gradual quality decay and therefore costs can rise if organizations fail to take proactive countermeasures. Quality control is the first step to avoiding this cost trap. Continuous quality assessments help…
While Microservices promise several beneficial characteristics for sustainable long-term software evolution, little empirical research covers what concrete activities industry applies for the evolvability assurance of Microservices and how…
A critical yet frequently overlooked challenge in the field of deepfake detection is the lack of a standardized, unified, comprehensive benchmark. This issue leads to unfair performance comparisons and potentially misleading results.…
Conformance checking is a set of process mining functions that compare process instances with a given process model. It identifies deviations between the process instances' actual behaviour ("as-is") and its modelled behaviour ("to-be").…
Parallel programming in high-performance computing depends on low-level APIs such as MPI, requiring users to manage synchronization and resources manually. Several correctness checking tools exist to help bug-free code development, though…